Vincel Hoang Ngoc Minh

36 papers B 5Journal 29Unranked 2
YearRankTypeTitle / Venue / Authors
2024 conf
SCSS (Work in Progress)
Vincel Hoang Ngoc Minh
2023 J jnl
Math. Comput. Sci.
Van Chiên Bui, Gérard H. E. Duchamp, Quoc Hoan Ngô, Vincel Hoang Ngoc Minh, Vu Nguyen Dinh
2021 J jnl
CoRR
Van Chiên Bui, Gérard Duchamp, Quoc Hoan Ngô, Vincel Hoang Ngoc Minh, Vu Nguyen Dinh
2020 J jnl
CoRR
Gérard H. E. Duchamp, Vincel Hoang Ngoc Minh, Vu Nguyen Dinh
2019 J jnl
Theor. Comput. Sci.
Gérard H. E. Duchamp, Vincel Hoang Ngoc Minh, Quoc Hoan Ngô
2018 B conf
CASC
Gérard H. E. Duchamp, Vincel Hoang Ngoc Minh, Karol A. Penson
2018 J jnl
CoRR
Vincel Hoang Ngoc Minh, Quoc Hoan Ngô, Gérard Henry Edmond Duchamp, V. Hoang, Ngoc Minh, Ngo Quoc, Phan Dang Luu, Kien An, Hai Phong, Viet Nam
2017 J jnl
J. Symb. Comput.
Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh, Quoc Hoan Ngô
2017 J jnl
J. Symb. Comput.
Van Chiên Bui, Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh
2017 J jnl
Discret. Math.
Gérard H. E. Duchamp, Jean-Yves Enjalbert, Vincel Hoang Ngoc Minh, Christophe Tollu
2016 J jnl
J. Symb. Comput.
Van Chiên Bui, Gérard Duchamp, Vincel Hoang Ngoc Minh, Ladji Kane, Christophe Tollu
2016 J jnl
CoRR
Ngoc Hoang, Gérard Duchamp, Vincel Hoang Ngoc Minh
2015 J jnl
CoRR
Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh, Christophe Tollu, Van Chiên Bui, Quoc Hoan Ngô
2015 J jnl
ACM Commun. Comput. Algebra
Van Chiên Bui, Gérard Duchamp, Vincel Hoang Ngoc Minh
2015 J jnl
ACM Commun. Comput. Algebra
Gérard Duchamp, Vincel Hoang Ngoc Minh, Quoc Hoan Ngô
2015 B conf
ISSAC
Van Chiên Bui, Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh
2013 J jnl
CoRR
Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh, Christophe Tollu, Bùi Chiên, Nguyen Hoang Nghia
2013 J jnl
CoRR
Gérard Henry Edmond Duchamp, Ladji Kane, Vincel Hoang Ngoc Minh, Christophe Tollu
2013 J jnl
ACM Commun. Comput. Algebra
Chen Bui, Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh
2013 J jnl
CoRR
Chen Bui, Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh
2012 J jnl
CoRR
Jean-Yves Enjalbert, Vincel Hoang Ngoc Minh
2012 J jnl
Discret. Math.
Jean-Yves Enjalbert, Vincel Hoang Ngoc Minh
2012 J jnl
ACM Commun. Comput. Algebra
Gérard H. E. Duchamp, Vincel Hoang Ngoc Minh
2011 conf
CAI
Matthieu Deneufchâtel, Gérard Duchamp, Vincel Hoang Ngoc Minh, Allan I. Solomon
2011 J jnl
CoRR
Matthieu Deneufchâtel, Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh, Allan I. Solomon
2010 J jnl
CoRR
Gérard Henry Edmond Duchamp, Vincel Hoang Ngoc Minh, Allan I. Solomon, Silvia Goodenough
2009 J jnl
J. Symb. Comput.
Christian Costermans, Vincel Hoang Ngoc Minh
2007 J jnl
J. Glob. Optim.
Tran Trang, Nguyen Cam Chi, Vincel Hoang Ngoc Minh
2005 B conf
PAKDD
Tran Trang, Nguyen Cam Chi, Vincel Hoang Ngoc Minh
2005 B conf
ISSAC
Christian Costermans, Jean-Yves Enjalbert, Vincel Hoang Ngoc Minh, Michel Petitot
2000 J jnl
Discret. Math.
Vincel Hoang Ngoc Minh, Michel Petitot
2000 J jnl
Discret. Math.
Vincel Hoang Ngoc Minh, Michel Petitot, Joris van der Hoeven
2000 J jnl
Discret. Math.
Vincel Hoang Ngoc Minh, Gérard Jacob
1998 B conf
ISSAC
Vincel Hoang Ngoc Minh, Michel Petitot, Joris van der Hoeven
1998 J jnl
Discret. Math.
Vincel Hoang Ngoc Minh
1991 J jnl
Theor. Comput. Sci.
Vincel Hoang Ngoc Minh
Docker-README.md
← Index Docker-README.md markdown
# REDB Docker Setup

This document describes the Docker containerization for the REDB malware analysis framework.

## Overview

REDB has been containerized as a single unified image that supports both feature extraction and decompilation analysis. The container is stateless, processes files from S3 or local mounts, and exports results to ClickHouse database or via API callbacks.

## Architecture

- **Single Unified Container**: One image handles both feature extraction and decompilation
- **Runtime Tool Installation**: Tools (CAPA, DIE, Binary Ninja) installed at runtime from host snapshots
- **Stateless Processing**: No persistent storage required between runs
- **Multiple Invocation Modes**: Supports `--nomad-job`, `--s3`, `--s3-solo`, and `--path` modes
- **External Dependencies**: Connects to external ClickHouse and S3 services

## Files Structure

```
├── Dockerfile                 # Single unified container definition
├── docker-build.sh            # Build script with Docker Desktop bug workaround
├── docker-push.sh             # Push script to registry
├── test-docker.sh             # Container testing script
├── test-nomad.sh              # Nomad job mode testing
├── .dockerignore              # Build context exclusions
└── scripts/
    └── setup-and-run.sh       # Runtime tool setup entrypoint
```

## Tool Installation Strategy

The container uses a **runtime installation** approach:

1. **Base Image**: Contains Python dependencies and REDB code
2. **Runtime Setup**: `scripts/setup-and-run.sh` configures tools at container start
3. **Host Snapshots**: Binary Ninja installed from `/opt/binaryninja` if available
4. **System Tools**: CAPA and DIE expected at `/usr/bin/capa` and `/usr/bin/nfdc`

## Build and Run

### 1. Build Container

```bash
# Build unified image
./docker-build.sh

# Manual build
docker build --platform linux/amd64 -f Dockerfile -t redb:latest .
```

### 2. Run Modes

#### Nomad Job Mode (Primary)
```bash
# Feature extraction
docker run --rm \
  -e JOB_ID="analysis_001" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="feature_extraction" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="BasicPropertiesExtractor,PEFeaturesExtractor" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e S3_ACCESS_KEY="your-key" \
  -e S3_SECRET_KEY="your-secret" \
  redb:latest python3 start.py --nomad-job

# Decompilation (same container, different flags)
docker run --rm \
  -e JOB_ID="analysis_002" \
  -e S3_KEY="samples/malware.exe" \
  -e S3_BUCKET="malware-bucket" \
  -e WORKER_TYPE="decompilation" \
  -e CALLBACK_URL="https://api.example.com/callbacks" \
  -e ANALYSIS_MODULES="all" \
  -v /opt/binaryninja:/opt/binaryninja:ro \
  redb:latest python3 start.py --nomad-job --decompile
```

#### S3 Solo Mode
```bash
# Process single sample by S3 key (standard sharded path)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Process private sample (with prepath)
docker run --rm \
  -e S3_BUCKET="samples-bucket" \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  -e S3_ENDPOINT="s3.example.com" \
  -e INDEX_PREFIX="redb" \
  -e REPO="test-analysis" \
  redb:latest python3 start.py --s3-solo "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

#### Local Files Mode
```bash
# Mount local samples
docker run --rm \
  -v /path/to/samples:/samples:ro \
  -v ./logs:/app/logs \
  -e CLICKHOUSE_HOST="clickhouse.example.com" \
  redb:latest python3 start.py --path /samples --repo local_test --index_prefix redb
```

## Environment Variables

### Required for Nomad Job Mode
- `JOB_ID` - Unique job identifier
- `S3_KEY` - S3 object key for sample
- `S3_BUCKET` - S3 bucket name
- `WORKER_TYPE` - "feature_extraction" or "decompilation"
- `CALLBACK_URL` - API endpoint for results
- `ANALYSIS_MODULES` - Comma-separated extractor list or "all"

### Database Configuration
- `CLICKHOUSE_HOST` - ClickHouse server hostname
- `CLICKHOUSE_PORT` - Port (default: 8123)
- `CLICKHOUSE_USER` - Database user (default: default)
- `CLICKHOUSE_PASSWORD` - Database password
- `CLICKHOUSE_DATABASE` - Database name (default: default)

### S3 Configuration
- `S3_ENDPOINT` - S3 endpoint URL
- `S3_ACCESS_KEY` - S3 access key
- `S3_SECRET_KEY` - S3 secret key
- `S3_SECURE` - "true" or "false" for HTTPS

### Processing Configuration
- `INDEX_PREFIX` - Database table prefix (default: redb)
- `REPO` - Repository identifier for this analysis batch
- `BATCH_SIZE` - Processing batch size (default: 10)
- `REDB_TIMEOUT` - Analysis timeout in seconds (default: 300)

### Tool Timeouts
- `CAPA_TIMEOUT` - CAPA analysis timeout (default: 300)
- `DIE_TIMEOUT` - DIE analysis timeout (default: 180)
- `BINJA_TIMEOUT` - Binary Ninja timeout (default: 1200)
- `DECOMPILE_EXTRACTOR_TIMEOUT` - Decompilation timeout (default: 2580)

## Binary Ninja Setup

For decompilation capabilities, mount Binary Ninja from host:

```bash
# Mount Binary Ninja installation
-v /opt/binaryninja:/opt/binaryninja:ro

# Mount license file
-v /path/to/license.dat:/home/analyzer/.binaryninja/license.dat:ro
```

The container will automatically detect and configure Binary Ninja at runtime.

## Registry Deployment

### Push to Registry
```bash
# Tag and push
./docker-push.sh

# Or manually
docker tag redb:latest your-registry/redb:latest
docker push your-registry/redb:latest
```

### Pull and Run
```bash
docker pull your-registry/redb:latest
docker run your-registry/redb:latest python3 start.py --nomad-job
```

## Testing

### Container Functionality Test
```bash
# Test with S3 key (standard sharded path)
./test-docker.sh "09/f7/09f7d02a3c2382199458c98a62b045145ee54ab6aba86166aecf3d10c3c1444c.zip"

# Test with private sample S3 key
./test-docker.sh "private/ab/cd/abcd1234567890abcdef1234567890abcdef1234567890abcdef123456.zip"
```

### Nomad Job Architecture Test
```bash
# Test Nomad job mode
./test-nomad.sh
```

## Development

### Interactive Container
```bash
# Debug container interactively
docker run -it --entrypoint /bin/bash redb:latest

# Check tool availability
docker run --rm redb:latest which python3
docker run --rm redb:latest ls -la /usr/bin/capa
```

### Build Troubleshooting

The build script includes workarounds for Docker Desktop bugs:

```bash
# If build hangs at "exporting to image", press Ctrl+C
# The image will still be created and tagged automatically
./docker-build.sh
```

### Container Logs
```bash
# View logs from mounted directory
docker run -v ./logs:/app/logs redb:latest python3 start.py --path /samples
tail -f logs/*.txt
```

## Production Notes

### Resource Requirements
- **Memory**: 2-4GB recommended (8GB for decompilation)
- **CPU**: 2+ cores recommended
- **Disk**: Minimal (stateless container)
- **Network**: Access to ClickHouse and S3 services

### Security
- Container runs as non-root user `analyzer` (UID 1000)
- Sample files should be mounted read-only
- No persistent state between container runs
- Isolated processing environment for malware analysis

### Deployment Architecture

This container is designed for:
- **Nomad job dispatch**: Single-use containers processing one sample each
- **Kubernetes jobs**: Batch processing with external orchestration
- **CI/CD pipelines**: Automated analysis in build systems
- **Development**: Local testing and debugging

The unified container approach means the same image handles both feature extraction and decompilation - the difference is only in the command-line flags used when starting the container.